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2306.08757
Cited By
InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models
14 June 2023
Yingheng Wang
Yair Schiff
Aaron Gokaslan
Weishen Pan
Fei Wang
Chris De Sa
Volodymyr Kuleshov
DiffM
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Papers citing
"InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models"
34 / 34 papers shown
Title
Addressing degeneracies in latent interpolation for diffusion models
Erik Landolsi
Fredrik Kahl
DiffM
47
0
0
12 May 2025
Revisiting Diffusion Autoencoder Training for Image Reconstruction Quality
Pramook Khungurn
Sukit Seripanitkarn
Phonphrm Thawatdamrongkit
Supasorn Suwajanakorn
DiffM
77
0
0
30 Apr 2025
Patronus: Bringing Transparency to Diffusion Models with Prototypes
Nina Weng
Aasa Feragen
Siavash Bigdeli
DiffM
41
0
0
28 Mar 2025
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Marianne Arriola
Aaron Gokaslan
Justin T Chiu
Zhihan Yang
Zhixuan Qi
Jiaqi Han
S. Sahoo
Volodymyr Kuleshov
DiffM
77
5
0
12 Mar 2025
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling
Xiao Li
Zekai Zhang
Xiang Li
Siyi Chen
Zhihui Zhu
Peng Wang
Qing Qu
DiffM
53
0
0
09 Feb 2025
Generative Modeling on Lie Groups via Euclidean Generalized Score Matching
Marco Bertolini
Tuan Le
Djork-Arné Clevert
DiffM
86
0
0
04 Feb 2025
Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models
Youngjun Jun
Jiwoo Park
Kyobin Choo
Tae Eun Choi
Seong Jae Hwang
CoGe
41
0
0
31 Oct 2024
Hierarchical Clustering for Conditional Diffusion in Image Generation
Jorge da Silva Goncalves
Laura Manduchi
Moritz Vandenhirtz
Julia E. Vogt
DiffM
26
0
0
22 Oct 2024
Feature-guided score diffusion for sampling conditional densities
Zahra Kadkhodaie
S. Mallat
Eero P. Simoncelli
DiffM
37
1
0
15 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis
Yue Song
Thomas Anderson Keller
Yisong Yue
Pietro Perona
Max Welling
DRL
36
0
0
07 Oct 2024
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series Forecasting
Siyang Li
Yize Chen
Hui Xiong
DiffM
AI4TS
33
0
0
03 Oct 2024
Unsupervised Composable Representations for Audio
Giovanni Bindi
P. Esling
DiffM
OCL
CoGe
34
0
0
19 Aug 2024
Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes
Jonathan D. McCart
Andrew R. Sedler
Christopher Versteeg
Domenick M. Mifsud
Mattia Rigotti-Thompson
C. Pandarinath
DiffM
SyDa
28
1
0
30 Jul 2024
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
Yilun Xu
Gabriele Corso
Tommi Jaakkola
Arash Vahdat
Karsten Kreis
39
12
0
03 Jul 2024
Diffusion Models and Representation Learning: A Survey
Michael Fuest
Pingchuan Ma
Ming Gui
Johannes S. Fischer
Vincent Tao Hu
Bjorn Ommer
DiffM
36
20
0
30 Jun 2024
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim
Kwanghyeon Lee
Minsang Park
Byeonghu Na
Il-Chul Moon
DiffM
44
2
0
27 May 2024
ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks
Zhangkai Wu
Xuhui Fan
Jin Li
Zhilin Zhao
Hui Chen
LongBing Cao
52
2
0
24 May 2024
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment
Xudong Yu
Chenjia Bai
Haoran He
Changhong Wang
Xuelong Li
40
6
0
07 Apr 2024
Training Unbiased Diffusion Models From Biased Dataset
Yeongmin Kim
Byeonghu Na
Minsang Park
Joonho Jang
Dongjun Kim
Wanmo Kang
Il-Chul Moon
30
19
0
02 Mar 2024
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement
Tao Yang
Cuiling Lan
Yan Lu
Nanning Zheng
DiffM
22
6
0
15 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Wasu Top Piriyakulkij
Yingheng Wang
Volodymyr Kuleshov
DiffM
40
1
0
05 Jan 2024
Diffusion Models With Learned Adaptive Noise
S. Sahoo
Aaron Gokaslan
Christopher De Sa
Volodymyr Kuleshov
DiffM
36
8
0
20 Dec 2023
SODA: Bottleneck Diffusion Models for Representation Learning
Drew A. Hudson
Daniel Zoran
Mateusz Malinowski
Andrew Kyle Lampinen
Andrew Jaegle
James L. McClelland
Loic Matthey
Felix Hill
Alexander Lerchner
DiffM
30
48
0
29 Nov 2023
Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation
Hang Li
Chengzhi Shen
Philip Torr
Volker Tresp
Jindong Gu
32
32
0
28 Nov 2023
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models
Zhaoyuan Yang
Zhengyang Yu
Zhiwei Xu
Jaskirat Singh
Jing Zhang
Dylan Campbell
Peter Tu
Richard Hartley
25
11
0
12 Nov 2023
Diffusion Based Causal Representation Learning
Amir Mohammad Karimi Mamaghan
Andrea Dittadi
Stefan Bauer
Karl Henrik Johansson
Francesco Quinzan
CML
DiffM
32
0
0
09 Nov 2023
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models
Tao Yang
Yuwang Wang
Yan Lv
Nanning Zh
DiffM
33
23
0
31 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou
Shaoan Xie
Guang-Yuan Hao
Shiming Chen
Erdun Gao
Xiwei Xu
Chen Wang
Liming Zhu
Lina Yao
Kun Zhang
AI4CE
57
11
0
29 Jan 2023
NashAE: Disentangling Representations through Adversarial Covariance Minimization
Eric C. Yeats
Frank Liu
David A. P. Womble
Hai Helen Li
CML
38
10
0
21 Sep 2022
Lossy Image Compression with Conditional Diffusion Models
Ruihan Yang
Stephan Mandt
DiffM
11
128
0
14 Sep 2022
Diffusion Models: A Comprehensive Survey of Methods and Applications
Ling Yang
Zhilong Zhang
Yingxia Shao
Shenda Hong
Runsheng Xu
Yue Zhao
Wentao Zhang
Bin Cui
Ming-Hsuan Yang
DiffM
MedIm
224
1,311
0
02 Sep 2022
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
368
5,811
0
29 Apr 2021
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
279
3,375
0
09 Mar 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
306
10,368
0
12 Dec 2018
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